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ztwd
- 电力系统在台稳定计算式电力系统不正常运行方式的一种计算。它的任务是已知电力系统某一正常运行状态和受到某种扰动，计算电力系统所有发电机能否同步运行 1运行说明： 请输入初始功率S0，形如a+bi 请输入无限大系统母线电压V0 请输入系统等值电抗矩阵B 矩阵B有以下元素组成的行矩阵 1正常运行时的系统直轴等值电抗Xd 2故障运行时的系统直轴等值电抗X d 3故障切除后的系统直轴等值电抗 请输入惯性时间常数Tj 请输入时段数N 请输入哪个时段发生故障Ni
lu_decompose
- 数值与符号计算LU分解法，运用LU分解函数求解Ax＝b的矩阵运算-numerical and symbolic computation LU decomposition, using LU decomposition function for Ax = b matrix operation
Matrix
- 给定n个矩阵{A1,A2,…,An}，其中Ai与Ai+1是可乘的，i=1,2,…,n-1。考察这n个矩阵的连乘积A1A2…An。由于矩阵乘法满足结合律，故计算矩阵的连乘积可以有许多不同的计算次序，这种计算次序可以用加括号的方式来确定。若一个矩阵连乘积的计算次序完全确定，则可以依此次序反复调用2个矩阵相乘的标准算法（有改进的方法，这里不考虑）计算出矩阵连乘积。若A是一个p×q矩阵，B是一个q×r矩阵，则计算其乘积C=AB的标准算法中，需要进行pqr次数乘。
GEE
- The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The fu
ldiv
- The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The fu
matrix
- Matrix operations solution of AX=B Jordan and newton Methods
Gauss_elimination
- Gauss Elimination Algorithm is used to solve linear equations in the form Ax=B, find rank of matrix and to find inverse of matrixes. The program is done in matlab platform.
art
- 用于解反问题的代数重建法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x-Algebraic solution of the inverse problem for the reconstruction of France, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
Matrix
- Matrix (TRANSPOSE , INVERSE , MATRIX INVERSION USING GAUSS-JORDAN REDUCTION AND Calculates the multiplication of two matrix A and B such that C=AB.
20104102125258460
- In this paper we discuss the problem of recovering the vertices of a planar polygon from its measured complex moments.Because the given, measured moments can be noisy, the recovered vertices are only estimates of the true ones. The literature offers
Ponytail
- How to Simulate A Ponytail - The Sample App This is a very simple Lagrange Multiplier constrained dynamics simulator to accompany my articles and lectures on How to Simulate a Ponytail. For more information, see http://chrishecker.com/H
plot3d_2
- This function produces an image of a 3D object defined by matrix a(l,m,n) in terms of voxels the image is a view after rotating the object by angles alfa and beta (in degree) b is the image and d is its ditance to the viewer matrix The first figure d
matrix
- //--显示矩阵，形参m为行，n为列 void MatrixDisplay(double *A,int m,int n) //--求矩阵转置，形参m为行，n为列,A转置后存为B void MatrixInverse(double *A,double *B, int m,int n) //--求矩阵相乘,A矩阵为[m,p],B矩阵为[p,n],C为[m,n] void MatrixMultiply(double *A,double *B,double *C ,i
B
- 在卫星精密定轨中，Y=BX+V，其中B矩阵又包含了观测几何矩阵和状态转移矩阵，本程序计算了B矩阵。-In Precise Orbit Determination, Y = BX+ V, which also contains the observation matrix B geometric matrix and the state transition matrix, the program to calculate the B matrix.
matrix
- 假设稀疏矩阵A和B均以三元组表作为存储结构，写出矩阵相加的算法，另设三元组表C存放结果矩阵。-Suppose sparse matrix A and B are triples as a storage structure of the table, write the sum matrix algorithm, a separate table triples storage of the results of C matrix.
matrix
- 本程序将让用户输入两个矩阵a和b，它们的阶数应该相等 让后实现矩阵加法，减法，乘法运算并输出结果。-This program will allow the user to enter two matrices a and b, they should be equal to the order after the realization of matrix addition, subtraction, multiplication and output.
the-solution-to-AX=B
- 对任意线性方程组AX=B，利用矩阵等价变换形成上三角矩阵，在利用高斯消元法中的回代过程简便的求解方程组AX=B的解。本程序是用MATLAB编写的，运行时只要输入矩阵A和B，即可得到方程的解。程序中有详细的注释，很好理解。本程序具有通用性。-For any system of linear equations AX = B, the use of equivalent transformation matrix to form the upper triangular matrix using G
matrix_gauss
- 輸入為AX=B的A、B矩陣及N(A的row數)M(B的行數) 經過後可得到A的反矩陣、X解-Input for the AX = B, A, B matrix and N (A s row number) M (B the number of rows) After the inverse matrix A obtained after, X solution
matrix_lu
- 輸入為AX=B的A、B矩陣及N(A的row數)M(B的行數) 經過後可得到A的反矩陣、X解-Input for the AX = B, A, B matrix and N (A s row number) M (B the number of rows) After the inverse matrix A obtained after, X solution
Gauss-Jordan-Matrix
- For inverting a matrix, Gauss-Jordan elimination is about as efficient as any other method. For solving sets of linear equations, Gauss-Jordan elimination produces both the solution of the equations for one or more right-hand side vectors b, and also